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Surface Fractal Analysis for Estimating the Fracture Energy Absorption of Nanoparticle Reinforced Composites

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Surface Fractal Analysis for Estimating the Fracture Energy Absorption of Nanoparticle Reinforced Composites Materials 2012, 5, 922-936; doi:10.3390/ma5050922 OPEN ACCESS materials ISSN 1996-1944 www.mdpi.com/journal/materials Article Surface Fractal Analysis for Estimating the Fracture Energy Absorption of Nanoparticle Reinforced Composites Brahmananda Pramanik *, Tezeswi Tadepalli and P. Raju Mantena Department of Mechanical Engineering, University of Mississippi, University, MS 38677, USA; E-Mails: [email protected] (T.T.); [email protected] (P.R.M.) * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel.: +1-662-915-5990; Fax: +1-662-915-1640. Received: 19 March 2012; in revised form: 8 May 2012 / Accepted: 11 May 2012 / Published: 23 May 2012 Abstract: In this study, the fractal dimensions of failure surfaces of vinyl ester based nanocomposites are estimated using two classical methods, Vertical Section Method (VSM) and Slit Island Method (SIM), based on the processing of 3D digital microscopic images. Self-affine fractal geometry has been observed in the experimentally obtained failure surfaces of graphite platelet reinforced nanocomposites subjected to quasi-static uniaxial tensile and low velocity punch-shear loading. Fracture energy and fracture toughness are estimated analytically from the surface fractal dimensionality. Sensitivity studies show an exponential dependency of fracture energy and fracture toughness on the fractal dimensionality. Contribution of fracture energy to the total energy absorption of these nanoparticle reinforced composites is demonstrated. For the graphite platelet reinforced nanocomposites investigated, surface fractal analysis has depicted the probable ductile or brittle fracture propagation mechanism, depending upon the rate of loading. Keywords: nanocomposites; low velocity punch-shear; fractured surface; digital microscopy; fractal dimension; fracture energy; fracture toughness 1. Introduction Nanocomposites are being considered for applications in marine structures subjected to blast waves and impact loading. Impact energy mitigation is a requirement for these structures. Characterizing energy absorption response of materials at higher strain rates has gained increasing attention from Materials 2012, 5 923 researchers. Figure 1 shows the fracture energy contribution as a part of the total absorbed energy during fracture propagation. It also indicates that a major portion of the total energy input to the system during loading is dissipated. Roughness of the fractured surface plays a major role in predicting fracture energy absorption. Figure 1. Contribution of fracture energy to the total energy absorption mechanism during low-velocity impact. Beginning with the pioneering work by Mandelbrot et al. [1], numerous investigators have focused on statistical characterization of the roughness of fractured surfaces [1–10]. It is now evident that the topography of crack surfaces can be described as being self-affine [10]. Self affinity is defined and well-described in the context of fractals by Mandelbrot [2]. As the crack propagates, the scale of tortuosity varies in different axes, which leads to fractal self-affinity of the fractured surface. Hence determining invariant fractal dimensionality of the surface becomes more tedious and multiple scaled-sampling dependent. Griffith states that brittle fracture occurs when the released strain energy is greater than the fracture energy required to create new fracture surfaces [11]. Consequently a more tortuous fractured surface indicates greater fracture energy absorption during crack propagation. Cherepanov et al. [3] discussed several achievements in the field of fractal geometry that influenced fracture mechanics. Hotar et al. [4] applied fractal geometry in combination with statistical tools for the classification of surface roughness. Mecholosky [5] showed how fractal geometry can be used in estimating the theoretical strength of materials based on crack tip geometry and generated fracture surface. The applicability of the fractal concept within fracture mechanics has also been discussed in several publications. Kozlov et al. [6] showed that the fundamental concepts of fractal fracture mechanics are applicable to polymeric composites. Rodrigues et al. [7] applied the concept of fractals to explain the crack deflection toughening mechanism in ceramic materials. Ficker [8] derived the relationship between mechanical strength and fractal characteristics of porous gels and verified with experimental data. Williford [9] expressed the similarity relationship between fracture energy and surface roughness using fractal dimensionality. Lu et al. [9,12–14] extended Williford’s work to explain the uncertainties of predicting surface fractal dimensionality and illustrated (Figure 2) that the intuitive sense of tougher materials having rougher fracture surface is not commensurate with Materials 2012, 5 924 experimental observations. The relationships between roughness of fracture surfaces measured by fractal dimensions and toughness are exactly opposite for ductile and brittle materials. Composite materials are reported to have both possibilities. Figure 2. Relationship between fractal dimension of the fractured surface and fracture energy of different materials [9,12–14]. Objective of the work presented here is to quantify fractal dimensionality of the failure surfaces for predicting the fracture energy and toughness of vinyl ester based nanocomposites. The methodologies of estimating fractal dimension of the fractured surfaces are based on the classical Vertical Section Method (VSM) and the Slit Island Method (SIM) described in literature [3]. For our work these conventional methodologies have been adapted such that a digital microscope may be utilized to capture the surface images, which are then digitally processed to create the roughness profiles required for VSM, and the 2D cross sections required for SIM. This eliminates specimen preparation difficulties and increases repeatability. Energy absorption due to fracture and toughness under quasi-static uni-axial tensile and low velocity punch-shear loading is estimated analytically from the surface fractal dimension. To verify the validity of these two procedures, conventional hot rolled A36 steel and grey cast iron specimens that fractured under quasi-static axial tensile loading are also analyzed. A study is conducted to quantify the sensitivity of both fracture energy and predicted fracture toughness to the fractal dimension of the failed surface profile. An investigation on the viscoelastic response of similar nanocomposites reported that the storage modulus varies with temperature as well as frequency in multi-frequency Dynamic Mechanical Analyzer (DMA) [15]. Frequency dependent storage modulus indicates the possibility of different failure characteristics of nanoparticle reinforced composites at varied loading rates. The application of fractal analysis has been considered in the current research to observe the post-failure characteristics of nanocomposite specimens subjected to two different loading rates, i.e., quasi-static and low velocity punch-shear tests. The research findings reported in later sections demonstrate the applicability of surface fractal analysis for nanocomposites. Materials 2012, 5 925 2. Experimental Section 2.1. Materials and Methods of Investigation Pure Derakane 510A-40 brominated vinyl ester polymer is reinforced with 1.25 wt % xGnP (exfoliated graphite nanoplatelates) and 2.5 wt % xGnP in two different batches. Two batches are modified with a 10 wt % CTBN (Carboxy Terminated Butadiene Nitrile) rubbery toughening agent. The exfoliation and homogeneous dispersion of the nanoplatelets in polymer matrix are performed using sonication technique [16]. Coupons of these four different nanocomposite configurations are tested in quasi-static axial tensile and low velocity punch-shear loading according to ASTM standards D638 and D3763 respectively, and the improvement of mechanical properties is compared with respect to the pristine Derakane 510A-40 brominated vinyl ester polymer samples [17,18]. Specimens that are tested under low velocity punch-shear loading along with the corresponding material properties are shown in Table 1. Table 1. Specimens tested in low velocity punch-shear loading with the corresponding quasi-static uniaxial tensile properties used for estimating fracture energy and fracture toughness [17,18]. Type of Elastic Ultimate strength Types of matrix reinforcement modulus (GPa) (MPa) Brominated 510A-40 None 3.35 73.45 Vinyl ester Brominated 510A-40 1.25 wt % xGnP 3.67 40.96 Vinyl ester Brominated 510A-40 2.5 wt % xGnP 3.38 41.96 Vinyl ester Brominated 510A-40 1.25 wt % xGnP + 3.48 44.58 Vinyl ester 10 wt % CTBN Brominated 510A-40 2.5 wt % xGnP + 4.68 27.68 Vinyl ester 10 wt % CTBN Materials 2012, 5 926 2.2. Vertical Section Method The fracture surfaces of failed specimens are studied with a Keyence VHX-600E digital microscope [19] which generates a series of 3D-images (Figure 3a) at optical magnifications of 500×, and 1000× to 5000× with 1000× increment. Global slope of the cracked surface may also contribute to the variation in computed fractal dimension. At each magnification level, the profile roughness (Figure 3b) is estimated by the ratio (RL) of vertical section profile length (obtained from 3D Profile Measurement Software, VHX-H2MK Ver 1.1) to a fixed projection length of 50 μm, consistent for all cases. Surface roughness (RS) is calculated using the following expression [3]: 4 R = ()R −1 +1 s π L (1) The calibration factor,
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